- Hardware
- Processor
- CPU
- GPU
- FPGA
- ASIC
- Memory
- Storage
- Networking
- Server Software
AI Infrastructure Market size is valued at USD 29.2 billion in 2021 and is expected to grow at a CAGR of 25.3% during the forecast period 2022 to 2028. The global market provides a detailed overview of the AI infrastructure market, which can be segmented by offering, technology, function, deployment type, end user, and region. By offering, the AI Infrastructure market has been segmented into hardware, processor, CPU, GPU, FPGA, ASIC, memory, storage, networking, and server software. The hardware segment procured the maximum revenue share in the AI infrastructure market in 2021. Processors, storage, memory, and interconnects are hardware components required to create an AI infrastructure. Small in size, more effective, and more potent xeromorphic chip-based systems are expected to display huge hardware devices in the upcoming years due to the rapid advancement of technology. By technology, the AI Infrastructure has been segmented into machine learning and deep learning. The machine learning segment registered the largest revenue share in the AI infrastructure market in 2021 and is anticipated to lead the market owing to its aids in the development of new goods and provides businesses with a picture of trends in consumer behavior and operational business patterns. An important portion of the operations of numerous of today’s top businesses, like Google, Facebook, and Uber, revolve around machine learning. By function, the AI Infrastructure market has been segmented into training and inference. The training segment accounted for a significant revenue share in the AI infrastructure market in past years and is expected to have a significant revenue share in upcoming years. By deployment type, the AI Infrastructure market has been segmented into on-premises, cloud, and hybrid. The cloud deployment mode segment held the highest revenue share in the AI infrastructure market owing to reduced operational expenses, fuss-free deployment, high scalability, fast data accessibility, easy access to crucial data, and low capital requirements are just a few benefits of cloud deployment mode. Based on the end user, the segment has been segregated into the enterprise, government organizations, and cloud service providers. The enterprise segment acquired a significant revenue share in the AI infrastructure market in past years and would expect to maintain its dominance throughout the forecasted period by the usage of artificial intelligence across numerous businesses around the world. Key Development: In July 2022, Google entered into a partnership with Northwell Health, the largest healthcare system in New York. This partnership focused to use Google’s machine learning (ML), artificial intelligence (AI), and cloud capabilities. In addition, the partnership would intensify the health system’s digital transformation by utilizing cloud technology and artificial intelligence (AI), to enhance clinician experience, patient care, and operational efficiency. In May 202, Google Cloud announced Vertex AI, a new managed machine learning platform that is meant to make it easier for developers to deploy and maintain their AI models. In Dec 2021, Oracle Corporation acquired Cerner Corporation, an American supplier of health information technology services, devices, and hardware. This acquisition aimed to assist Oracle to scale up its cloud business in the hospital and health system market.
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Rising demand for AI software and hardware among various establishments in order to keep up with the increasing volume of data created by applications, advanced AI solutions frequently need new hardware and software. These AI-based solutions, for instance, require updates regarding the annotation and collection of data sources, as well as the creation, processing, and fine-tuning of models when more data becomes available. Deep learning, a branch of AI technology, has grown up to be one of the most significant computational workloads for businesses and will increase the usage of AI infrastructure.
The key factors driving the growth of the AI infrastructure market include growing data traffic, increasing need for high computing power, rising adoption of cloud-based machine learning platforms, increasingly large and complex datasets, growing focus on parallel computing in AI data centres, a rise in the cross-industry partnerships and collaborations, and increasing adoption of AI due to the COVID-19 pandemic.
The global AI infrastructure market is valued at USD 29.2 billion in 2021 and is expected to grow at a CAGR of 25.3% during the forecast period 2022 to 2028.
Investment and acquisition are the two key strategies opted for by the leading companies in the market.
Based on technology, the machine learning segment is expected to account for the largest share of the AI Infrastructure market during the forecast period, owing to its increasing usage in big companies.